The advent of portable integrated computing devices has caused a wide proliferation of cameras and video devices. These integrated computing devices commonly take the form of smartphones or tablets and typically include general purpose computers, cameras, sophisticated user interfaces including touch sensitive screens, and wireless communications abilities through WiFi, Long Term Evolution (LTE), High Speed Downlink Packet Access (HSDPA) and other cell-based or wireless technologies (WiFi is a trademark of the Wi-Fi Alliance, LTE is a trademark of the European Telecommunications Standards Institute (ETSI)). The wide proliferation of these integrated devices provides opportunities to use the devices' capabilities to perform tasks that would otherwise require dedicated hardware and software. For example, as noted above, integrated devices such as smartphones and tablets typically have one or two embedded cameras. These cameras generally amount to lens/camera hardware modules that may be controlled through the general purpose computer using firmware and/or software (e.g., “Apps”) and a user interface, e.g., including a touch-screen interface and/or touchless control, such as voice control.
The integration of cameras into communication devices such as smartphones and tablets has enabled people to share images and videos in ways never before possible. It is now very popular to acquire and immediately share images and/or videos with other people by either sending the photos via text message, by SMS, by email, though Apps, or by uploading the photos to an Internet-based website, such as a social networking site or a photo sharing site. User often desire to apply one or more corrective or artistic filters to their images and/or videos before sharing them with other users or posting them to Internet-based websites. Some such filters may modify the images in a content-independent fashion, e.g., a vignetting effect that darkens the outer borders of the image. Other filters may perform one or more color or brightness mapping techniques to improve the appearance of the image. Still other filters may manipulate each pixel in a programmatically-defined fashion to create a particular “effect,” e.g., an antique image effect or a black and white effect.
However, more and more, users desire the ability to apply more complex artistic effects to their captured images and/or video that do not simply perform a mathematical mapping of each pixel value in the image to generate an output image, but instead use artificial intelligence to imbue the ‘essence’ of a particular artistic style to their captured images and/or video. One such approach for applying artistic styles to images has been proposed in Gatys et al., “A Neural Algorithm of Artistic Style,” arXiv:1508.06576v2 [cs.cV], 2 Sep. 2015 (which paper is hereby incorporated by reference and referred to hereinafter as, “Gatys,”) and provides a neural algorithm that separates and recombines the content and style of arbitrary images to synthesize artistic versions of the input images. However, the algorithm proposed in Gatys takes a significant amount of time to apply an artistic style to a single image, and also requires a substantial amount of processing power, which is not typically available on users' personal electronic devices.
Due to the substantial time and processing requirements imposed by the Gatys algorithm, the assembly of a stylized video sequence of any substantial length in time (e.g., comprising more than a few dozen frames of video) is not feasible, given the time and processing constraints faced by personal electronic devices. Moreover, a naïve application of the artistic style transfer techniques of Gatys to each image in a sequence of images results in an assembled video sequence that has an undesirable amount of random ‘jitter’ or ‘flicker’ around moving and non-moving objects in the images due, at least in part, to the stochastic nature of the style transfer process. Moreover, it would also be desirable for users to be able to extract artistic styles from a portion comprising less than the entire source image (i.e., rather than using entire images as the artistic sources) and using the style extracted from said portion to automatically content-correct one or more undesired artifacts in a target image, or even in another portion of the source image.